Partition an image into a set of disjoint clusters

This function partitions an image into a set of disjoint clusters using k-means clustering.

Usage

partition(x, k, ...)

# S4 method for class 'LogicalNeuroVol,integer'
partition(x, k)

# S4 method for class 'LogicalNeuroVol,numeric'
partition(x, k)

# S4 method for class 'DenseNeuroVol,numeric'
partition(x, k)

Arguments

x

the image to partition, represented as a 3D array.

k

the number of clusters to form.

...

additional arguments passed to the kmeans function.

Value

a 3D array where each voxel is assigned to a cluster.

See also

kmeans

Examples

# Load an example 3D image
library(neuroim2)
img <- read_vol(system.file("extdata", "global_mask_v4.nii", package = "neuroim2"))

# Partition the image into 5 clusters using default options
clusters <- partition(img, 5)